2 results match your criteria: "Yasar Universitesi[Affiliation]"
Article Synopsis
- Machine learning models using big data are being applied in marketing to extract valuable insights from customer data and improve decision-making through better demand forecasting.
- There is limited research on how marketing strategies, particularly advertising, impact demand, highlighting the need for accurate forecasting models in business sustainability.
- This article evaluates various machine learning and deep learning techniques, concluding that Long Short Term Memory (LSTM) provides the best accuracy in predicting demand based on advertising expenses.
Using system dynamics to assess the environmental management of cement industry in streaming data context.
Sci Total Environ
May 2020
Plymouth Business School, Plymouth, University of Plymouth, Drake Circus Plymouth Devon, PL4 8AA, United Kingdom. Electronic address:
The cement industry can be regarded as one of the major sources of anthropogenic air pollution. It uses a significant amount of energy while creating substantial amount of potentially health-threatening carbon monoxide (CO), sulfur dioxide (SO), nitrogen oxides (NO) and dust particles. Hence, the cement industry can be regarded as a primary area for study in the development of green manufacturing.
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